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From motor to sensory processing in mirror neuron computational modelling

机译:镜像神经元计算建模中的从运动到感觉处理

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摘要

Typical patterns of hand-joint covariation arising in the context of grasping actions enable one to provide simplified descriptions of these actions in terms of small sets of hand-joint parameters. The computational model of mirror mechanisms introduced here hypothesizes that mirror neurons are crucially involved in coding and making this simplified motor information available for both action recognition and control processes. In particular, grasping action recognition processes are modeled in terms of a visuo-motor loop enabling one to make iterated use of mirror-coded motor information. In simulation experiments concerning the classification of reach-to-grasp actions, mirror-coded information was found to simplify the processing of visual inputs and to improve action recognition results with respect to recognition procedures that are solely based on visual processing. The visuo-motor loop involved in action recognition is a distinctive feature of this model which is coherent with the direct matching hypothesis. Moreover, the visuo-motor loop sets the model introduced here apart from those computational models that identify mirror neuron activity in action observation with the final outcome of computational processes unidirectionally flowing from sensory (and usually visual) to motor systems.
机译:在抓紧动作的上下文中出现的典型的手关节协变模式使人们能够根据少量的手关节参数来提供这些动作的简化描述。本文介绍的镜像机制的计算模型假设镜像神经元在编码中至关重要,并使简化的运动信息可用于动作识别和控制过程。尤其是,抓取动作识别过程是根据可见运动回路建模的,该回路使人们能够重复使用镜像编码的运动信息。在涉及可抓握动作分类的模拟实验中,发现镜像信息简化了视觉输入的处理,并改善了仅基于视觉处理的识别程序的动作识别结果。动作识别中涉及的视觉运动回路是该模型的显着特征,与直接匹配假设相一致。此外,视觉运动回路将此处介绍的模型与那些识别动作观察中的镜像神经元活动的计算模型分开,将计算过程的最终结果从感觉(通常是视觉)单向流向运动系统。

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